A fundamental question of security analysis is: When is a behavior normal, and when is it not? We present techniques that extract behavior patterns from thousands of apps—patters that represent normal behavior, such as “A travel app normally does not access stored text messages”. Combining data flow analysis with app ...

We present sandbox mining, a technique to confine an application to resources accessed during automatic testing. Sandbox mining first explores software behavior by means of automatic test generation, and extracts the set of resources accessed during these tests. This set is then used as a sandbox, blocking access to ...

One of the major tasks in maintaining software systems is understanding how specific effects came to be. This is especially true for effects that cause major harm, and especially challenging for causes that actively prevent discovery. We introduce Malfor, a system that, for any reliably reproducible and observable effect, ...

Softwaretechnik basiert wie jede andere Wissenschaft auf historischen Erfahrungen: Was hat in der Vergangenheit funktioniert und was nicht? Aus der Entstehungsgeschichte eines Programms, wie sie in Software-Archiven aufgezeichnet wurde, kann man solche Erfahrungen bilden und nutzbar machen – etwa um verwandte Programmstellen ...

The assessment of information flows is an essential part of analyzing Android apps, and is frequently supported by static taint analysis. Its precision, however, can suffer from the analysis not being able to precisely determine what elements a pointer can (and cannot) point to. Recent advances in static analysis suggest ...

To assess the behavior of a program, one needs to understand its inputs---their sources, their structure, and how they lead to individual behavior. But as syntax and semantics of inputs are almost never completely specified, humans and computers constantly have to figure out how to produce a particular behavior. In this ...

Program failures are often caused by faulty inputs (e.g. due to data corruption). When an input induces failure, one needs to debug the input data, i.e. isolate faults to obtain valid input data. Typically, debuggers focus on diagnosing faults in the program, rather than the input. This talk instead presents an approach ...

To exhaustively test a program, we need inputs that the program does not reject. Such valid inputs must satisfy syntactic and semantic constraints of the input language. Grammar-based fuzzers efficiently produce syntactically valid system inputs but miss context-sensitive semantic constraints. Example semantic properties ...